Covariate Effect Visualizer

Analyzer

Visualize covariate effects on PK parameters as a forest plot. Assess clinical significance with equivalence bounds. Free, instant, with AI interpretation.

PK Parameter Name

Effect Type

Reference Patient Sliders

Lower Bound

Upper Bound

Reference Lines

BE Bounds (0.80-1.25): 0.8Reference (1.0): 1

Covariate Effects (ref = 1.0)

Covariate

Est

Covariate

Est

Covariate

Est

Covariate

Est

Covariate

Est

Covariate

Est

Results

Summary

1 significant, 2 potentially significant, 3 not significant out of 6 covariates

Clinically Significant

Potentially Significant

Not Significant

Parameter

Significant

1.000

Potentially Significant

2.000

Not Significant

3.000

Forest Plot — CL

Weight (>90 kg vs 70 kg)

1.15 [1.02–1.3]

Age (>65 yr vs 40 yr)

0.92 [0.82–1.03]

Renal Impairment (Mild)

1.28 [1.08–1.52]

Hepatic Impairment (Mild)

1.05 [0.88–1.25]

Female vs Male

0.95 [0.86–1.05]

Asian vs Caucasian

1.08 [0.92–1.27]

For educational and research purposes only. Not intended as medical advice. Always verify calculations independently and consult qualified healthcare professionals. See our Terms of Service for full details.

Educational Content